Downhole formation fluid sampling tools, often called formation testing tools, operate to draw, and sometimes test, fluid samples from formations. Useful measurements can be made on these fluid samples while the tool is downhole, and/or upon samples that are retained and brought uphole.
When a fluid sample is taken in a hydrocarbon bearing zone, it can be very useful to determine properties of the hydrocarbon sample, for example viscosity and/or molecular composition. However, existing techniques are limited in their ability to determine these properties. For example, viscosity can be predicted from the damping of a vibrating mechanical instrument, but such measurements downhole require that the device operate in a difficult environment that is not conducive to reliable and accurate operation of the device. A nuclear magnetic resonance (NMR) tool can be employed in a formation testing tool (see, for example, U.S. Pat. No. 6,111,408), and NMR measurements on formation fluids can provide information from which properties of the fluids can be inferred. Because petroleum fluids are complex mixtures containing many different kinds of hydrocarbon molecules, the accurate prediction of viscosity and composition for arbitrary temperature (T) and pressure (P) is difficult. One approach is to use physics models or correlations that relate the physical property being predicted to NMR measurements using an equation containing empirically determined parameters.
An example of a technique for the prediction of viscosity of formation fluids from NMR measurements of relaxation time (T1 and T2) and diffusion coefficient (D) distributions is based on empirical correlations (see Morriss et al., SPWLA Annual Transactions, p. 1–24, Jun. 19–22, 1994; Freedman et al., SPE Journal (75325), December 2001; Lo et al., SPE Journal (77264), March 2002). The correlations relate the logarithmic means of the distributions to viscosity using empirically determined constants. The accuracy of the viscosities predicted from these correlations is limited by three factors: (1) the detailed shape of the distributions is not accounted for (2) the empirical constants used in the correlations are not universal and can vary by as much as a factor of two for different oils and (3) the assumed form for the correlation equations is not strictly accurate.
Molecular composition can be very coarsely estimated in downhole fluid sampling tools using optical density measurements as a function of wavelength for radiation in the near infrared region (see Fujisawa et al., SPE 84092, presented at the 2003 SPE ATCE meeting). The technique uses principal component regression analysis to predict molecular groupings, i.e., C1, C2–C5, and C6+. Physics based parametric models have been proposed to predict molecular composition of crude oils from NMR measurements of relaxation time and diffusion coefficient distributions (see Heaton and Freedman U.S. Patent Publication, 2003-0128032-A1). However, it is difficult using physics models to properly account for different molecular shapes (e.g., aromatic and aliphatic hydrocarbon molecules), pressure and temperature effects, and dissolved gases.
It is among the objects of the present invention to provide a method for determination of formation fluid characteristics which overcomes shortcomings of prior art approaches.